Structural analysis of regional logistics network based on weighted network

doi:10.3778/j.issn.1002-8331.2009.26.074

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (26): 245-248.DOI: 10.3778/j.issn.1002-8331.2009.26.074

• 工程与应用 • Previous Articles

Structural analysis of regional logistics network based on weighted network

YANG Guang-hua^1,2，LI Xia-miao¹，XIE Xiao-liang¹

1.School of Traffic & Transportation Engineering，Central South University，Changsha 410075，China
2.Hunan Communication Polytechnic College，Changsha 410004，China

Received:2009-02-09 Revised:2009-03-13 Online:2009-09-11 Published:2009-09-11
Contact: YANG Guang-hua

加权区域物流网络结构分析

杨光华^1,2，李夏苗¹，谢小良¹

1.中南大学交通运输工程学院，长沙 410075
2.湖南交通职业技术学院，长沙 410004

通讯作者: 杨光华

Abstract

Abstract: It can understand the macro-level characteristics of regional logistics to analyze structure of regional logistics network.The paper，assigning the magnitudes of logistics to network，constitutes regional logistics network based on the weighted network，and makes quantitative analysis to structural characteristics of regional logistics network from four perspectives：node degree and strength，edge weight disparity，weight clustering and node degree correlations.To an example of Hunan province，it finds a few characteristics of logistics node weight disparity been more，same kind mixed network and so on，indicating the weighted network can reveal more structure characteristics of regional logistics network.

Key words: weighted network, regional logistics, structure, Hunan province

摘要： 分析区域物流网络结构能了解物流宏观层面特征。把物流量赋予网络上，构建基于加权网络的区域物流网络。从节点度和强度分布、边的权重差异度、加权集聚性、节点度相关性等对区域物流网络结构进行定量分析。并以湖南省为例，发现其区域内物流节点强度和边差异度大、为同类混合网络等特征，这表明加权网络可以揭示更多区域物流网络的结构特征。

关键词: 加权网络, 区域物流, 结构, 湖南省

CLC Number:

F252.8

YANG Guang-hua^1,2，LI Xia-miao¹，XIE Xiao-liang¹. Structural analysis of regional logistics network based on weighted network[J]. Computer Engineering and Applications, 2009, 45(26): 245-248.

杨光华^1,2，李夏苗¹，谢小良¹. 加权区域物流网络结构分析[J]. 计算机工程与应用, 2009, 45(26): 245-248.

[1]	WANG Jinyu, YANG Haitao, LI Gaoyuan, ZHANG Changgong, FENG Bodi. Research Progress of Generative Adversarial Network and Its Application in Image Processing [J]. Computer Engineering and Applications, 2021, 57(8): 26-35.
[2]	WANG Bing, LE Hongxia, LI Wenjing, ZHANG Menghan. Mask Detection Algorithm Based on Improved YOLO Lightweight Network [J]. Computer Engineering and Applications, 2021, 57(8): 62-69.
[3]	DU Yao. Android Malicious Family Detection Algorithm Based on Local Optimization Matching [J]. Computer Engineering and Applications, 2021, 57(8): 84-90.
[4]	MA Qiaomei, WANG Mingjun, LIANG Haoran. License Plate Location Detection Algorithm Based on Improved YOLOv3 in Complex Scenes [J]. Computer Engineering and Applications, 2021, 57(7): 198-208.
[5]	YANG Fengyu, HUANG Yaxuan, ZHOU Shijian, ZHENG Wei. Survey of Software Defect Prediction Combined with Multi-metrics [J]. Computer Engineering and Applications, 2021, 57(5): 10-24.
[6]	LAI Jun, WEI Jingyi, CHEN Xiliang. Overview of Hierarchical Reinforcement Learning [J]. Computer Engineering and Applications, 2021, 57(3): 72-79.
[7]	CHEN Liu, CHEN Mingju, XUE Zhishuang, LUO Shisheng. Lightweight and High-Precision Convolutional Neural Network for Helmet Recognition Method [J]. Computer Engineering and Applications, 2021, 57(22): 177-181.
[8]	XIE Junzhang, PENG Hui, TANG Jianfeng, HOU Yichen, ZENG Qingxi. Improved YOLOv4 for Dense Remote Sensing Target Detection [J]. Computer Engineering and Applications, 2021, 57(22): 247-256.
[9]	ZHANG Rongxia, WU Changxu, SUN Tongchao, ZHAO Zengshun. Progress on Deep Reinforcement Learning in Path Planning [J]. Computer Engineering and Applications, 2021, 57(19): 44-56.
[10]	ZHAN Ling, ZHANG Yiwen. Design and Implementation of SCM and SSD Based Key-Value Store [J]. Computer Engineering and Applications, 2021, 57(19): 97-103.
[11]	YANG Yanjiao, ZHAO Guotao, WANG Pidong. Sentence Similarity Calculation Method Based on Semantics and Emotion [J]. Computer Engineering and Applications, 2021, 57(16): 151-158.
[12]	ZUO Baochuan, ZHANG Qing. Feature Guidance Mechanism for Saliency Detection Network [J]. Computer Engineering and Applications, 2021, 57(14): 201-208.
[13]	HU Renyuan, LIU Jianhua, BU Guannan, ZHANG Dongyang, LUO Yixuan. Research on Sentiment Analysis of Multi-level Semantic Collaboration Model Fused with BERT [J]. Computer Engineering and Applications, 2021, 57(13): 176-184.
[14]	REN Yichen, XIAO Da. Similarity Analysis of Malicious Programs Based on Two Dimensional Characteristics of Programs [J]. Computer Engineering and Applications, 2021, 57(1): 118-125.
[15]	ZHOU Tao, LU Huiling, HUO Bingqiang. Survey of Deep Belief Network [J]. Computer Engineering and Applications, 2020, 56(9): 24-32.

Structural analysis of regional logistics network based on weighted network

加权区域物流网络结构分析

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics